In-store shopping event monitoring and analysis can provide direct evidence of shopper behavior at the point of product selection. Prior monitoring systems recorded video of shoppers, and used human operators to interpret the video. Such systems suffer from the drawback that they generate large amounts of data due to the high frame rate at which conventional video is captured, and require significant time spent by human operators to analyze the data. As a result, these systems have been costly to implement.